import pandas as pd
import plotly.express as px

Issues found in data

Province-wise data

1. Week 31 is missing in WHO weekly situation updates.
2. In the 47th week, the death graph shows sudden spike. It is because uncounted deaths from the past one year were added in that week. Actual figures of deaths can be seen for each day in the MOHP's website.

Age-wise data

1. Age-wise data of first seven weeks are not included in WHO situation updates.
2. Age group classification is not uniform in two weeks (11 and 12).

province = pd.read_csv('province_wise_master_data.csv')
age = pd.read_csv('age_wise_master_data.csv')

COVID-19 Data disaggregated province-wise

Total cumulative cases

fig = px.line(province, x="Date", y="Total Cumulative Cases", color='Province')
fig.show()

Total cumulative deaths

fig = px.line(province, x="Date", y="Total Cumulative Deaths", color='Province')
fig.show()

Week-wise number of cases

fig = px.line(province, x="Date", y="Number of Cases", color='Province')
fig.show()

COVID-19 Data disaggregated age-wise

Total cumulative cases

fig = px.line(age, x="Date", y="Total Cumulative Cases", color='Age Group')
fig.show()

Week-wise number of cases

fig = px.line(age, x="Date", y="Number of Cases", color='Age Group')
fig.show()

Total cumulative deaths - Male

fig = px.line(age, x="Date", y="Cumulative_Death_Male", color='Age Group')
fig.show()

Total cumulative deaths - Female

fig = px.line(age, x="Date", y="Cumulative_Death_Female", color='Age Group')
fig.show()